Engagement of non-government organisations and community care workers in collaborative TB/HIV activities including prevention of mother to child transmission in South Africa: Opportunities and challenges
Bibliographic record
Abstract
BACKGROUND: The implementation of collaborative TB/HIV activities may help to mitigate the impact of the dual epidemic on patients and communities. Such implementation requires integrated interventions across facilities and levels of government, and with communities. Engaging Community Care Workers (CCWs) in the delivery of integrated TB/HIV services may enhance universal coverage and treatment outcomes, and address human resource needs in sub-Saharan Africa. METHODS: Using pre-intervention research in Sisonke district, KwaZulu-Natal, South Africa as a case study, we report on three study objectives: (1) to determine the extent of the engagement of NGOs and CCWs in the implementation of collaborative TB/HIV including PMTCT; (2) to identify constraints related to provision of TB/HIV/PMTCT integrated care at community level; and (3) to explore ways of enhancing the engagement of CCWs to provide integrated TB/HIV/PMTCT services. Our mixed method study included facility and NGO audits, a household survey (n = 3867), 33 key informant interviews with provincial, district, facility, and NGO managers, and six CCW and patient focus group discussions. RESULTS: Most contracted NGOs were providing TB or HIV support and care with little support for PMTCT. Only 11% of facilities' TB and HIV patients needing care and support at the community level were receiving support from CCWs. Only 2% of pregnant women reported being counseled by CCWs on infant feeding options and HIV testing. Most facilities (83%) did not have any structural linkage with NGOs. Major constraints identified were system-related: structural, organizational and managerial constraints; inadequate CCW training and supervision; limited scope of CCW practice; inadequate funding; and inconsistency in supplies and equipment. Individual and community factors, such as lack of disclosure, stigma related to HIV, and cultural beliefs were also identified as constraints. CONCLUSIONS: NGO/CCW engagement in the implementation of collaborative TB/HIV/PMTCT activities is sub-optimal, despite its potential benefits. Effective interventions that address contextual and health systems challenges are required. These should combine systematic skills-building, an enhanced scope of practice and consistent CCW supervision with a reliable referral and monitoring and evaluation system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".